关键词: 遥感影像, 目标分割, 舰船检测, 显著性, 海陆分离

Abstract: Ship detection algorithms applied to high-resolution optical remote sensing images are put forward. These algorithms are in order to solve the problem of high false alarm rate in traditional ship detection method in high-resolution optical remote sensing images. Two-dimensional image entropy which can describe the spatial texture feature is used to separate ocean and land combined with the principle of region growing. Visual saliency model is introduced in ship object segmentation. This method can solve the problem of unable to segment dark polarity ship target in ship target segmentation phase. The segmentation accuracy is higher in most background modes. Finally, in the segment candidate regions, multi-feature comprehensive method is adopted to eliminate false alarms. Results show that this method has higher detection rate and lower false alarm rate in ship target detection.

Key words: remote sensing image, object segmentation, ship detection, saliency, sea-land segmentation